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st: Re: use mfx to compute marginal effects in tobit
Dear All,
Further to my previous query, I estimate a tobit model and then use "mfx" to
compute marginal effects of variables. Strangely, the computed marginal
effects for all the variables are the same as the estimated cofficient in
the probit model. It seems "mfx" does not function. But I found it does
function following a probit model (i.e., generating the same marginal
effects as that is generated from "dprobit").
I enclose the model output using two variables for your information.
Thanks
Hong Zou
----- Original Message -----
From: "Zou Hong" <[email protected]>
To: <[email protected]>
Sent: Wednesday, August 08, 2007 9:35 AM
Subject: st: Re:tobit model robust standard errors and marginal effects
Dear All,
I want to report the results from estimating a Tobit model (left censored
at zero) using robust standard errors and marginal effects (which by
default are evaluated at the sample mean of variables).
I have done a search and found that somebody suggesting using "intreg" to
get the robust standard errors and p-values. For marginal effects,
somebody suggested using dtobit, dtobit2 and/or mfx. However, it seems
these routines do not allow for the use of robust standard errors.
I wonder how I can report a Tobit model using robust standard errors and
marginal effects at the same time? Can I use "intreg" and request "robust"
option, followed by "mfx"?
Many thanks
Hong Zou
----- Original Message -----
From: "Nick Cox" <[email protected]>
To: <[email protected]>
Sent: Wednesday, August 08, 2007 4:27 AM
Subject: RE: st: RE: mlogit problem with "predict"
-stripplot- from SSC will let you
compare variables in groups.
stripplot pc1-pc4, by(tax)
gives you one graph, not four. See
the help for further options.
Nick
[email protected]
Maarten buis
--- Sheela Athreya <[email protected]> wrote:
> The idea that maybe I have an (almost) perfect prediction occurred
> to me too, but I don't know how to investigate it. Perhaps there is
> an equivalent test to -tab tax pc- that allows me to look at
> quantitative variables for anything that is off?
One option is to look at dotplots:
dotplot pc1, over(tax) median
dotplot pc2, over(tax) median
dotplot pc3, over(tax) median
dotplot pc4, over(tax) median
They give you simultaneously an idea about the strength of the
association and the number of observations in each category.
*
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*
* For searches and help try:
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* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
Attachment:
tobit marginal effects output.pdf
Description: Adobe PDF document